Predicting Time-Lag Stock Return Using Tactical Asset Allocation Trading Strategies Across Global Stock Indices

Abstract

This paper investigates the effectiveness of different tactical asset allocation trading strategies on global stock market indices in order to better forecast the returns. It has been revealed that timing model strategies are appeared to be the best performing one than the passive buy and hold strategy. Results show that the simulated moving average is the best strategy in order to generate buy and sell signals to minimize the investor’s risk and maximize the return of the portfolio. It has been recommended that investors who are looking to minimize the risk of their portfolio and decrease the drawdown can use the proposed timing model strategy to achieve a balanced portfolio in the future.

Value-at-Risk Analysis for Measuring Stochastic Volatility of Stock Returns: Using GARCH-Based Dynamic Conditional Correlation Model

“…Higher market risk is because of the presence of unpredictability or volatility in stock prices. The reason for high volatility in stock returns is always the unstable country's conditions, both politically and economically (Afzal et al, 2019). Increasing market risk on stock has brought new challenges to find an effective way of predicting risk in dynamic conditions.…”